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  • Applying Machine Learning Algorithms to Identify Problematic Nuclear Data within Nuclear Transport Simulations

    Creator:
    Grechanuk, Pavel A.
    Abstract:
    The primary goal of this dissertation is to improve the quality of nuclear data available to the nuclear science community. We propose to accomplish this by applying machine learning algorithms to the large number of available benchmark experiments and simulations, with the goal of determining which nuclear data have strong...
    Resource Type:
    Dissertation
    Full Text:
    Simulations Abstract approved: Todd S. Palmer The primary goal of this dissertation is to improve the

  • A statistical inference framework for finding recurring patterns in large data with applications to energy management

    Creator:
    You, Zeyu
    Abstract:
    We consider the problem of finding unknown patterns that are recurring across multiple sets. For example, finding multiple objects that are present in multiple images or a short DNA code that is repeated across multiple DNA sequences. We first consider a simple problem of finding a single unknown pattern in...
    Resource Type:
    Masters Thesis
    Full Text:
    . . . . . . . . . . . . . . . . . . . 3 3.1 (a) Our setting: each set Xi is assumed to contain one instance of a desired element s. Our

  • Towards Direct Simultaneous Speech Translation

    Creator:
    Chen, Junkun
    Abstract:
    Simultaneous speech translation (SimulST) is widely useful in many cross-lingual communication scenarios, including multinational conferences and international traveling. Since text-based simultaneous machine translation (SimulMT) has achieved great success in recent years. The conventional cascaded approach for SimulST uses a pipeline of streaming ASR followed by simultaneous MT but suffers from...
    Resource Type:
    Dissertation
    Full Text:
    reported in Inaguma et al. [46]. Pino et al. [73] use extra D′s,y which includes Librispeech (Ds,x) and

  • Parsing with Recurrent Neural Networks

    Creator:
    Cross, James Henry, III
    Abstract:
    Machine learning models for natural language processing have traditionally relied on large numbers of discrete features, built up from atomic categories such as word forms and part-of-speech labels, which are considered completely distinct from each other. Recently however, the advent of dense feature representations coupled with deep learning techniques has...
    Resource Type:
    Dissertation
    Full Text:
    -standard dependency parsing system [42]. Stack S is a list of heads, j is the start index of the queue, and

  • Towards Narrative Understanding with Deep Neural Networks and Hidden Markov Models

    Creator:
    Orr, J. Walker
    Abstract:
    Narratives are central to communication and the human experience. For a computer system to understand a narrative, it must be able to identify the key facts or plot elements that describe what happened or how the world has changed. These element are called events;establishing a document’s events and the relationships...
    Resource Type:
    Dissertation
    Full Text:
    taken from ACE2005’s annotation, is also embedded starting with a random initialization. These

  • Information-theoretic Approach to Design and Evaluate Privacy-preserving and Fair Frameworks for Continuous High-dimensional Data

    Creator:
    Alsulaimawi, Zahir Ahmed Hussein
    Abstract:
    Deep learning is becoming the latest trend in sensitive applications, such as healthcare, criminal justice, and finance. As these new applications emerge, adversaries are circumventing them. Further, there have been concerns about the possibility of bias and discrimination in predictive applications. In order to address these issues, we propose an...
    Resource Type:
    Dissertation
    Full Text:
    by observing in- termediate variable(s), i.e., RVs (X ,Z,Y ) satisfy separation if X ⊥ Y | Z (X and

  • Novelty Detection Under the Multi-Instance Multi-Label Framework

    Creator:
    Lou, Qi
    Abstract:
    Novelty detection plays an important role in machine learning and signal processing. This project studies novelty detection in a new setting where the data object is represented as a bag of instances and associated with multiple class labels, referred to as multi-instance multi-label (MIML) learning. Contrary to the common assumption...
    Resource Type:
    Capstone Project
    Full Text:
    applied to novelty detection to learn a function f that is positive on a subset S of the input space and

  • A study of methods for fine-grained object classification of arthropod specimens

    Creator:
    Lin, Junyuan
    Abstract:
    Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
    Resource Type:
    Masters Thesis
    Full Text:
    material are those of the author(s) and do not necessarily reflect the views of the National Science

  • Data Classification and Extraction of Weather Reports

    Creator:
    Qin, Rui
    Abstract:
    Severe weather in the United States causes huge insured losses to crop and property frequently.It creates major impact and elicit diverse response in the weather insurance industry. Events like hail, storm, hurricane etc. are more likely to cause catastrophe losses. So it becomes crucial to collect and analyze these extreme...
    Resource Type:
    Capstone Project
    Full Text:
    research staff: Dr. Christopher Daly and Dylan Keon, for their insightful suggestions and feedback. Last

  • Relation extraction with automatic ontonotes annotation and ETC

    Creator:
    Sauer, Andrew
    Abstract:
    Intuitively, it seems as though natural language processing tasks might benefit from explicit representations of the syntactic and semantic properties of text. Ontonotes is a dataset which attempts to annotate texts, to represent as much as possible of the meaning of the text explicitly within the annotation. Many tools exist...
    Resource Type:
    Honors College Thesis
    Full Text:
    parsing features [6]. As an example of the format from Wikipedia, “John loves Mary” becomes: (S (NP (NNP